Improving semantic interoperability of big data for epidemiological surveillance

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    Abstract

    Future disease outbreaks may spread faster and stronger than recent epidemics, such as Zika, Ebola and Influenza. The integration of multiple existing Early Warning Systems (EWS) is a requirement to support disease surveillance in combating infectious disease outbreaks. In this direction, numerous applications have been developed considering big data from diverse sources. However, big data potential can only be exploited if interoperability challenges are addressed. In this paper we discuss a semantic interoperability problem when using data exchanging standards for EWS integration. Particularly, we identify an issue regarding the distinction between the concepts of situation and event in the Emergency Data Exchange Language (EDXL), the OASIS set of standards for disaster management. To cope with interoperability issues we propose an ontology-driven situation-aware approach for the development and integration of EWS. The approach leverages on the OntoEmerge core ontology, in which we incorporate the clear distinction between the concepts of situation and event.
    Original languageEnglish
    Title of host publicationEnterprise Interoperability in the Digitized and Networked Factory of the Future, I-ESA 2016
    EditorsMartin Zelm, Guy Doumeingts, Joao Pedro Mendonca
    Place of PublicationUK
    PublisherInternational Society for Technology in Education
    Pages314-324
    Number of pages11
    ISBN (Print)9781847040442
    Publication statusPublished - Mar 2016
    EventInternational Conference on Interoperability for Enterprise Systems and Applications, I-ESA 2016 - Guimaraes, Portugal
    Duration: 29 Mar 20161 Apr 2016

    Conference

    ConferenceInternational Conference on Interoperability for Enterprise Systems and Applications, I-ESA 2016
    Abbreviated titleI-ESA
    CountryPortugal
    CityGuimaraes
    Period29/03/161/04/16

    Keywords

    • SCS-Services
    • Ontology
    • EWI-27322
    • Disease surveillance
    • Disaster risk reduction
    • IR-102591
    • Situation awareness
    • EDXL
    • Early warning system
    • METIS-319465
    • Semantic Interoperability

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  • Cite this

    Moreira, J., van Sinderen, M. J., Ferreira Pires, L., & Dockhorn Costa, P. (2016). Improving semantic interoperability of big data for epidemiological surveillance. In M. Zelm, G. Doumeingts, & J. P. Mendonca (Eds.), Enterprise Interoperability in the Digitized and Networked Factory of the Future, I-ESA 2016 (pp. 314-324). UK: International Society for Technology in Education.